// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#define EIGEN_NO_STATIC_ASSERT

#include "main.h"

template<bool IsInteger>
struct adjoint_specific;

template<>
struct adjoint_specific<true>
{
	template<typename Vec, typename Mat, typename Scalar>
	static void run(const Vec& v1, const Vec& v2, Vec& v3, const Mat& square, Scalar s1, Scalar s2)
	{
		VERIFY(test_isApproxWithRef(
			(s1 * v1 + s2 * v2).dot(v3), numext::conj(s1) * v1.dot(v3) + numext::conj(s2) * v2.dot(v3), 0));
		VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2), s1 * v3.dot(v1) + s2 * v3.dot(v2), 0));

		// check compatibility of dot and adjoint
		VERIFY(test_isApproxWithRef(v1.dot(square * v2), (square.adjoint() * v1).dot(v2), 0));
	}
};

template<>
struct adjoint_specific<false>
{
	template<typename Vec, typename Mat, typename Scalar>
	static void run(const Vec& v1, const Vec& v2, Vec& v3, const Mat& square, Scalar s1, Scalar s2)
	{
		typedef typename NumTraits<Scalar>::Real RealScalar;
		using std::abs;

		RealScalar ref =
			NumTraits<Scalar>::IsInteger ? RealScalar(0) : (std::max)((s1 * v1 + s2 * v2).norm(), v3.norm());
		VERIFY(test_isApproxWithRef(
			(s1 * v1 + s2 * v2).dot(v3), numext::conj(s1) * v1.dot(v3) + numext::conj(s2) * v2.dot(v3), ref));
		VERIFY(test_isApproxWithRef(v3.dot(s1 * v1 + s2 * v2), s1 * v3.dot(v1) + s2 * v3.dot(v2), ref));

		VERIFY_IS_APPROX(v1.squaredNorm(), v1.norm() * v1.norm());
		// check normalized() and normalize()
		VERIFY_IS_APPROX(v1, v1.norm() * v1.normalized());
		v3 = v1;
		v3.normalize();
		VERIFY_IS_APPROX(v1, v1.norm() * v3);
		VERIFY_IS_APPROX(v3, v1.normalized());
		VERIFY_IS_APPROX(v3.norm(), RealScalar(1));

		// check null inputs
		VERIFY_IS_APPROX((v1 * 0).normalized(), (v1 * 0));
#if (!EIGEN_ARCH_i386) || defined(EIGEN_VECTORIZE)
		RealScalar very_small = (std::numeric_limits<RealScalar>::min)();
		VERIFY((v1 * very_small).norm() == 0);
		VERIFY_IS_APPROX((v1 * very_small).normalized(), (v1 * very_small));
		v3 = v1 * very_small;
		v3.normalize();
		VERIFY_IS_APPROX(v3, (v1 * very_small));
#endif

		// check compatibility of dot and adjoint
		ref = NumTraits<Scalar>::IsInteger
				  ? 0
				  : (std::max)((std::max)(v1.norm(), v2.norm()),
							   (std::max)((square * v2).norm(), (square.adjoint() * v1).norm()));
		VERIFY(internal::isMuchSmallerThan(
			abs(v1.dot(square * v2) - (square.adjoint() * v1).dot(v2)), ref, test_precision<Scalar>()));

		// check that Random().normalized() works: tricky as the random xpr must be evaluated by
		// normalized() in order to produce a consistent result.
		VERIFY_IS_APPROX(Vec::Random(v1.size()).normalized().norm(), RealScalar(1));
	}
};

template<typename MatrixType>
void
adjoint(const MatrixType& m)
{
	/* this test covers the following files:
	   Transpose.h Conjugate.h Dot.h
	*/
	using std::abs;
	typedef typename MatrixType::Scalar Scalar;
	typedef typename NumTraits<Scalar>::Real RealScalar;
	typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
	typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
	const Index PacketSize = internal::packet_traits<Scalar>::size;

	Index rows = m.rows();
	Index cols = m.cols();

	MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3(rows, cols),
			   square = SquareMatrixType::Random(rows, rows);
	VectorType v1 = VectorType::Random(rows), v2 = VectorType::Random(rows), v3 = VectorType::Random(rows),
			   vzero = VectorType::Zero(rows);

	Scalar s1 = internal::random<Scalar>(), s2 = internal::random<Scalar>();

	// check basic compatibility of adjoint, transpose, conjugate
	VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1);
	VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(), m1);

	// check multiplicative behavior
	VERIFY_IS_APPROX((m1.adjoint() * m2).adjoint(), m2.adjoint() * m1);
	VERIFY_IS_APPROX((s1 * m1).adjoint(), numext::conj(s1) * m1.adjoint());

	// check basic properties of dot, squaredNorm
	VERIFY_IS_APPROX(numext::conj(v1.dot(v2)), v2.dot(v1));
	VERIFY_IS_APPROX(numext::real(v1.dot(v1)), v1.squaredNorm());

	adjoint_specific<NumTraits<Scalar>::IsInteger>::run(v1, v2, v3, square, s1, s2);

	VERIFY_IS_MUCH_SMALLER_THAN(abs(vzero.dot(v1)), static_cast<RealScalar>(1));

	// like in testBasicStuff, test operator() to check const-qualification
	Index r = internal::random<Index>(0, rows - 1), c = internal::random<Index>(0, cols - 1);
	VERIFY_IS_APPROX(m1.conjugate()(r, c), numext::conj(m1(r, c)));
	VERIFY_IS_APPROX(m1.adjoint()(c, r), numext::conj(m1(r, c)));

	// check inplace transpose
	m3 = m1;
	m3.transposeInPlace();
	VERIFY_IS_APPROX(m3, m1.transpose());
	m3.transposeInPlace();
	VERIFY_IS_APPROX(m3, m1);

	if (PacketSize < m3.rows() && PacketSize < m3.cols()) {
		m3 = m1;
		Index i = internal::random<Index>(0, m3.rows() - PacketSize);
		Index j = internal::random<Index>(0, m3.cols() - PacketSize);
		m3.template block<PacketSize, PacketSize>(i, j).transposeInPlace();
		VERIFY_IS_APPROX((m3.template block<PacketSize, PacketSize>(i, j)),
						 (m1.template block<PacketSize, PacketSize>(i, j).transpose()));
		m3.template block<PacketSize, PacketSize>(i, j).transposeInPlace();
		VERIFY_IS_APPROX(m3, m1);
	}

	// check inplace adjoint
	m3 = m1;
	m3.adjointInPlace();
	VERIFY_IS_APPROX(m3, m1.adjoint());
	m3.transposeInPlace();
	VERIFY_IS_APPROX(m3, m1.conjugate());

	// check mixed dot product
	typedef Matrix<RealScalar, MatrixType::RowsAtCompileTime, 1> RealVectorType;
	RealVectorType rv1 = RealVectorType::Random(rows);
	VERIFY_IS_APPROX(v1.dot(rv1.template cast<Scalar>()), v1.dot(rv1));
	VERIFY_IS_APPROX(rv1.template cast<Scalar>().dot(v1), rv1.dot(v1));

	VERIFY(is_same_type(m1, m1.template conjugateIf<false>()));
	VERIFY(is_same_type(m1.conjugate(), m1.template conjugateIf<true>()));
}

template<int>
void
adjoint_extra()
{
	MatrixXcf a(10, 10), b(10, 10);
	VERIFY_RAISES_ASSERT(a = a.transpose());
	VERIFY_RAISES_ASSERT(a = a.transpose() + b);
	VERIFY_RAISES_ASSERT(a = b + a.transpose());
	VERIFY_RAISES_ASSERT(a = a.conjugate().transpose());
	VERIFY_RAISES_ASSERT(a = a.adjoint());
	VERIFY_RAISES_ASSERT(a = a.adjoint() + b);
	VERIFY_RAISES_ASSERT(a = b + a.adjoint());

	// no assertion should be triggered for these cases:
	a.transpose() = a.transpose();
	a.transpose() += a.transpose();
	a.transpose() += a.transpose() + b;
	a.transpose() = a.adjoint();
	a.transpose() += a.adjoint();
	a.transpose() += a.adjoint() + b;

	// regression tests for check_for_aliasing
	MatrixXd c(10, 10);
	c = 1.0 * MatrixXd::Ones(10, 10) + c;
	c = MatrixXd::Ones(10, 10) * 1.0 + c;
	c = c + MatrixXd::Ones(10, 10).cwiseProduct(MatrixXd::Zero(10, 10));
	c = MatrixXd::Ones(10, 10) * MatrixXd::Zero(10, 10);

	// regression for bug 1646
	for (int j = 0; j < 10; ++j) {
		c.col(j).head(j) = c.row(j).head(j);
	}

	for (int j = 0; j < 10; ++j) {
		c.col(j) = c.row(j);
	}

	a.conservativeResize(1, 1);
	a = a.transpose();

	a.conservativeResize(0, 0);
	a = a.transpose();
}

EIGEN_DECLARE_TEST(adjoint)
{
	for (int i = 0; i < g_repeat; i++) {
		CALL_SUBTEST_1(adjoint(Matrix<float, 1, 1>()));
		CALL_SUBTEST_2(adjoint(Matrix3d()));
		CALL_SUBTEST_3(adjoint(Matrix4f()));

		CALL_SUBTEST_4(adjoint(MatrixXcf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2),
										 internal::random<int>(1, EIGEN_TEST_MAX_SIZE / 2))));
		CALL_SUBTEST_5(adjoint(
			MatrixXi(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
		CALL_SUBTEST_6(adjoint(
			MatrixXf(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));

		// Complement for 128 bits vectorization:
		CALL_SUBTEST_8(adjoint(Matrix2d()));
		CALL_SUBTEST_9(adjoint(Matrix<int, 4, 4>()));

		// 256 bits vectorization:
		CALL_SUBTEST_10(adjoint(Matrix<float, 8, 8>()));
		CALL_SUBTEST_11(adjoint(Matrix<double, 4, 4>()));
		CALL_SUBTEST_12(adjoint(Matrix<int, 8, 8>()));
	}
	// test a large static matrix only once
	CALL_SUBTEST_7(adjoint(Matrix<float, 100, 100>()));

	CALL_SUBTEST_13(adjoint_extra<0>());
}
